Installation
edvart
is distributed as a Python package via PyPI.
It can be installed using pip
:
$ pip install edvart
We recommend using Poetry for dependency management.
To add edvart
into a Poetry environment, add the following snippet
to the pyproject.toml
environment definition file:
[tool.poetry.dependencies] python = ">=3.8, <3.12" edvart = "4.0.0"
Extras
Edvart has an optional dependency umap
, which adds a plot called UMAP
to Multivariate Analysis.
To install Edvart with the optional umap
dependency via pip, run the following command:
$ pip install "edvart[umap]"
To install Edvart with the optional extra using Poetry, replace the snippet
of the pyproject.toml
environment file above with the following snippet:
[tool.poetry.dependencies] python = ">=3.8, <3.12" edvart = { version = "4.0.0", extras = ["umap"] }
Rendering Plotly Interactive Plots
Edvart uses Plotly to render interactive plots.
JupyterLab
To display interactive plots which use Plotly in JupyterLab, you need to install some JupyterLab extensions.
The extension jupyter-dash
needs to be installed in order for Plotly plots
to be rendered correctly in JupyterLab.
It can be simply installed as a Python package, e.g. via pip
:
pip install jupyter-dash
to install plotly-dash to a Poetry environment, add the following line
under tool.poetry.dependencies
in the pyproject.toml
environment definition file:
jupyter-dash = "^0.4.2"
See https://plot.ly/python/getting-started/ for more information.
Visual Studio Code
The following extensions need to be installed to display Plotly interactive plots in Visual Studio Code notebooks:
- Jupyter
is required to run Jupyter notebooks in Visual Studio Code.
- Jupyter Notebook Renderers
is required to render Plotly plots in Visual Studio Code notebooks.